I. Field of the Invention
The present invention relates to code division multiple access (CDMA) including multicarrier CDMA (MC-CDMA) used for scintillation, dispersion, fading, and multipath environments and other variations to CDMA, orthogonal frequency division multiple access (OFDMA), and orthogonal Wavelet division multiple access (OWDMA) for cellular telephone and wireless data communications with data rates up to multiple T1 (1.544 Mbps) and higher (>100 Mbps), and to optical CDMA. Applications are mobile, point-to-point and satellite communication networks, data compression, pattern recognition, media image compression and processing, and radar More particularly, the present invention relates to the application of CDMA, OFDMA, and OWDMA to multiple input transmit and multiple output receive (MIMO) cellular communications using high speed downlink (or uplink) packet access (HSPDA), IEEE 802.16d WiMax, IEEE 802.11g Wi-Fi, IEEE 802.15 UWB, 3G, 4G, and the other cellular standards.
II. Description of the Related Art
Current cellular communications representative networks are illustrated in FIG. 1 with a schematic layout of part of a cellular network which depicts cells 1,2,3,4 that partition this portion of the area coverage of the network, depicts a user (network user) 5 located within a cell with forward and reverse communications links 6 with the cell-site base station (access point/hub) 7, depicts the base station communication links 8 with the MSC (mobile switching center) or the WSC (wireless switching center) 9, and depicts the MSC/WSC communication links with another base station (access point/hub) 17, with another MSC/WSC 16, and with external elements 10,11,12,13,14,15. One or more base stations are assigned to each cell or multiple cells or sectors of cells depending on the application. One of the base stations 9 in the network serves as the MSC/WSC which is the network system controller and switching and routing center that controls all of user timing, synchronization, and traffic in the network and with all external interfaces including other MSC's. External interfaces could include satellite 10, PSTN (public switched telephone network) 11, LAN (local area network) 12, PAN (personal area network) 13, UWB (ultra-wideband network) 14, and optical networks 15. As illustrated in the figure, base station 7 is the nominal cell-site station for cells i−2, i−1, i, i+1 identified as 1,2,3,4, which means it is intended to service these cells with overlapping coverage from other base stations (access points/hubs). The cell topology and coverage depicted in the figure are intended to be illustrative and the actual cells could be overlapping and of differing shapes. Cells can be sub-divided into sectors. Not shown are possible subdivision of the cells into sectors and/or combining the cells into sectors. Each user in a cell or sector communicates with a base station which should be the one with the strongest signal and with available capacity. When mobile users cross over to other cells and/or are near the cell boundary a soft handover scheme is employed for CDMA in which a new cell-site base station is assigned to the user while the old cell-site base station continues to service the user for as long as required by the signal strength.
Improvements in data rate and/or spatial diversity for application to cellular communications including the communications links 6 in FIG. 1 between a user 5 located within a cell with forward and reverse communications with the cell-site access point/hub (base station) 7, have been demonstrated with the use of multiple-input multiple-output MIMO systems. MINO applies to scenarios which have random scintillation, dispersion, fading, and multipath communication links (channels) with low-correlation statistics, that ensures some of the channels will be independent and can support higher data rates and/or path diversity.
FIG. 2 depicts a representative MIMO scenario for N transmit (Tx) antennas and M receive (Rx) antennas for the forward communications link for cellular communications 6 from the access point or hub 7 to the network user 5 in FIG. 1. Antenna elements for Tx include the digital-to-analog conversion, modulator, up-converter, transmit amplifier and antenna elements, and for Rx include the antenna elements, down-conversion, demodulator, analog-to-digital conversion, and symbol detection. All links use the same frequency spectrum unless noted. Both data rate increase and/or spatial diversity require the solution of a linear set of equations which measure the transmission coefficients between the input signals X 13 to the N Tx antennas 15 and the received output signals Y 17 from the M Rx antennas 16.
In FIG. 2 transmission starts with the input Tx data d 11 which is encoded, interleaved, formatted, and symbol encoded 12 to generate the input signal (symbol) vector X 13 whose elements are the encoded data symbols from 12. Turbo encoding provides the best performance over the fading and scintillated links and is one of several choices including convolutional and block encoding. Tx symbol vector X is handed over to a space-time encoder 14 whose output is the space-time code C followed by symbol modulation and hand-over to the Tx processing for transmission by the Tx antennas 15. The N Tx antenna transmissions over the fading and scintillation paths 16 are received by the M Rx antennas and each Tx-to-Rx link is a communications channel. Statistics of these Tx-to-Rx communications channels are assumed to be relatively constant over a usable burst of communications which means the data burst can be demodulated at the Rx receiver knowing the set of channel transmission coefficients {hij=h(i,j)} where hij=h(i,k) is the complex coefficient measuring the amplitude and phase change of the channel between the transmit Tx antenna “i” and the received Rx antenna “j” which is due to transmission path scintillation, dispersion, fading, multipath, and anomalies other than the direct path transmission propagation loss in clear air. These channel coefficients are elements of the M×N transmission matrix H=[hij=h(i,k)] which means the Rx signal (symbol) vector Y 17 is defined by the MIMO equation Y=H∘X+No for each symbol set or time epoch T when there is no space-time coding and where Y is M×1, H is M×N, X is N×1, “∘” is a multiply operation, M×N is the size of the M by N matrix, M×1 is an M×1 dimension vector, N×1 is an N by 1 dimension vector, and No is the additive noise seen in the Rx receiver which includes the Rx link, thermal, amplifier, and signal processing noise sources. For a burst of T symbol sets with no diversity the dimensions increase to M×T matrix Y, N×T matrix X, and M∘T×N∘T matrix H which is constructed such that each column vector Y(i) of Y and each column vector X(i) of X are related by the system equation Y(i)=H•X(i) for T=i symbol set. Symbol set time intervals T or epochs T measure the sequencing of the input signal sets. With space-time encoding for diversity applications the MIMO equation is over T>1 time epochs for each symbol set whereupon the MIMO equation is Y=H•C+No where the space-time code matrix C includes the components of X and extends over these time epochs for each symbol set. The Rx signal Y 17 is space-time decoded to generate the estimate {circumflex over (X)} 27 of X which is then de-interleaved and turbo decoded 18 to generate the Rx estimate {circumflex over (d)} 19 of the transmitted data d. Space-time decoding only applies to diversity applications and for data rate increases the space-time decoding is replaced by a de-multiplexing operation.
MIMO applications are grouped into data rate and diversity improvements. Data rate improvement R is the ratio of the data rate with MIMO to the data rate with a single Tx-to-Rx communications link where data rate is in bits per second. Diversity improvement L is the order or degree of diversity equal to the number of parallel and independent Tx-to-Rx communication channels provided by MIMO for each user. Bound on data rate improvement is R≦min(M,N), bound on diversity is L≦max(M,N)/R, constraints on the scenario include the requirement M≦N/T in order to have a solvable set of linear equations, and for the data rate increase R>1 applications where M>N the full rank of rank (H′•H) is a necessary condition for a unique solution for the estimate {circumflex over (X)} of X as a linear equation in the Y where H′ is the conjugate transpose of H.
Diversity applications of MIMO use space-time coding techniques to encode the Tx data X and spread the data over the available links and over T>1 epochs with the space-time code matrix C. This is considered to be a fundamental requirement for MIMO systems in order to provide improved performance in fading, provide less susceptibility to interference, and provide lower data packet dropout rates. Conventional dispersive delay-line receivers use weighted taps against multipath which creates dispersive and frequency selective channels. Current research includes the development of super-orthogonal space-time codes wherein “super-orthogonality” refers to the use of set partitioning of the data bits which are mapped by differential phase shift keying (DPSK), phase shift keying (PSK), quadrature amplitude modulation (QAM), Gaussian minimum shift keying (GMSK), or other modulation onto the amplitude and complex plane of each symbol, and the development of various properties and design algorithms for space-time codes for MIMO applications. Listed patents relate to MIMO technologies and applications and listed IEEE technical papers and press books compile the vast amount of research on space-time coding for both block codes and trellis codes and for equalization with emphasis on turbo coding techniques for MIMO applications. The current work on algorithms for solving the MIMO system equation Y=H∘X+No for {circumflex over (X)} includes the “Special Issue on MIMO Wireless Communications”, IEEE Trans. on Signal Processing, November 2003, Vol. 51, No. 11, the “Special Issue on Space-Time Transmission, Reception, Coding and Signal Processing”, IEEE Trans. on Info. Theory, October 2003, Vol. 49, No. 10, the “MIMO Systems and Applications, Part I”, the IEEE Journal on Selected Areas in Communications, April 2003, Vol. 21, No. 3, and listed papers and articles. Estimates {circumflex over (X)} of X include direct inversion, maximum likelihood (ML), minimum mean square error (MMSE), and various iterative algorithms that trade off reduced computational complexity with some loss of accuracy. The best solution is generally considered to be the ML unbiased minimum variance solution to the estimate {circumflex over (X)}=min{∥Y−H∘X∥2} which is the value of {circumflex over (X)} that minimizes the square of the absolute value of the error δX=Y−H∘X in the estimate {circumflex over (X)}=X+δX, and when the space-time code is explicitly identified this estimate is {circumflex over (X)}=min{∥Y−H•C∥2}. Current practice does not explicitly identify C in the formulation of the MIMO problem.
For diversity, several space-time codes and in particular space-time block codes have been developed with the goal of providing relatively simple implementations of the optimal ML decoder for a few number of antennas. One group of such schemes concatenates this space-time code with an outer trellis coded modulation (TCM) code. This allows the combined space-time and TCM codes to use classic set partitioning techniques to partition signals within each block code subset and this supports a simple decision rule that restricts the transition branches leaving from or arriving to each state to be labeled by code words from the same block code subset.
For data rate increase, the use of spatial multiplexing as a form of space-time block coding transmits individual streams of data with each stream assigned to a different Tx antenna, after each data stream has been encoded and interleaved. With this V-BLAST scheme “V-BLAST: An architecture for realizing very high data rates over the rich-scattering wireless channel” by Wolniansky et. al. in Proc. URSI Int. Symp. Signals, Systems, Electronics, Pisa, Italy, September-October 1998 pp. 295-300, there is no spreading of the data over each of the antennas as in the diversity schemes, although there may be some mixing of the data over the different Tx antennas in a variation of V-BLAST. In general for data rate increase the receiver must de-multiplex the received channel signals and recover estimates of the transmitted signal in one of several possible ways. Zero-forcing techniques use a straight matrix inversion and can give degraded results when H is ill-conditioned meaning that the H′∘H for M<N has less than full rank, and/or the ratio of maximum to minimum eigenvalues of H′∘H is too large, and/or the determinant det(H′∘H) of H′∘H is too small. A MMSE receiver may be of help for this situation. On the other hand, the optimum detection and turbo decoding method used in the receiver is ML which compares all possible combinations of input data symbols which could have been transmitted, with the observed symbols in executing the estimate {circumflex over (X)}=min{∥Y−H•C∥2}=min{∥Y−H•X∥2}). Complexity of this decoding is high when many antennas or high-order modulations are used. Enhanced variants of this decoding have been proposed recently. The original BLAST scheme “Wireless communications system having a space-time architecture employing multi-element antennas at both the transmitter and receiver”, U.S. Pat. No. 6,317,466 Nov. 13, 2001, Foschini and Golden, Lucent Technologies Inc. and variations thereof have received considerable attention. With BLAST the decoding strategy proposed is nulling and canceling which gives a reasonable tradeoff between complexity and performance. The matrix inversion process in nulling and canceling is performed in layers where one estimates a column from H, subtracts the symbol estimates from Y, and continues the decoding successively. A lien on this algorithm is the residual noise from each iteration which introduces a noise floor on decoding performance.
Critical to these algorithms for both diversity and data rate increase, is the accurate measurements of channel transmission coefficients which measure the fading and scintillation path loss, the Rayleigh flat fade and the Rician K-factor distribution modeling of this path loss, shadowing, doppler and delay spread profiles, joint correlations between the Tx antennas and between the Rx antennas, and the channel matrix H singular value (eigenvalue) distributions.